research
∙
09/19/2023
Unbiased Parameter Estimation for Partially Observed Diffusions
In this article we consider the estimation of static parameters for part...
share
research
∙
09/06/2023
Multilevel Particle Filters for a Class of Partially Observed Piecewise Deterministic Markov Processes
In this paper we consider the filtering of a class of partially observed...
research
∙
04/30/2023
A Class of Spatial Filtering Problems with Unknown Spatial Observations
We consider a class of high-dimensional spatial filtering problems, wher...
research
∙
02/20/2023
An Improved Unbiased Particle Filter
In this paper we consider the filtering of partially observed multi-dime...
research
∙
01/29/2023
Antithetic Multilevel Particle Filters
In this paper we consider the filtering of partially observed multi-dime...
research
∙
11/01/2022
Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion
In this paper we consider Bayesian parameter inference for partially obs...
research
∙
08/08/2022
Unbiased Estimation of the Vanilla and Deterministic Ensemble Kalman-Bucy Filters
In this article we consider the development of an unbiased estimator for...
research
∙
06/14/2022
Unbiased Estimation using the Underdamped Langevin Dynamics
In this work we consider the unbiased estimation of expectations w.r.t. ...
research
∙
03/24/2022
Multilevel Bayesian Deep Neural Networks
In this article we consider Bayesian inference associated to deep neural...
research
∙
03/10/2022
Multi-index Sequential Monte Carlo ratio estimators for Bayesian Inverse problems
We consider the problem of estimating expectations with respect to a tar...
research
∙
03/07/2022
Convergence Speed and Approximation Accuracy of Numerical MCMC
When implementing Markov Chain Monte Carlo (MCMC) algorithms, perturbati...
research
∙
03/06/2022
Unbiased Estimation using a Class of Diffusion Processes
We study the problem of unbiased estimation of expectations with respect...
research
∙
12/27/2021
Unbiased Parameter Inference for a Class of Partially Observed Levy-Process Models
We consider the problem of static Bayesian inference for partially obser...
research
∙
10/02/2021
A Lagged Particle Filter for Stable Filtering of certain High-Dimensional State-Space Models
We consider the problem of high-dimensional filtering of state-space mod...
research
∙
09/06/2021
Unbiased Estimation of the Hessian for Partially Observed Diffusions
In this article we consider the development of unbiased estimators of th...
research
∙
08/09/2021
Multilevel Estimation of Normalization Constants Using the Ensemble Kalman-Bucy Filter
In this article we consider the application of multilevel Monte Carlo, f...
research
∙
08/02/2021
Improved efficiency of multilevel Monte Carlo for stochastic PDE through strong pairwise coupling
Multilevel Monte Carlo (MLMC) has become an important methodology in app...
research
∙
07/05/2021
Randomized multilevel Monte Carlo for embarrassingly parallel inference
This position paper summarizes a recently developed research program foc...
research
∙
05/24/2021
Unbiased Estimation of the Gradient of the Log-Likelihood for a Class of Continuous-Time State-Space Models
In this paper, we consider static parameter estimation for a class of co...
research
∙
05/11/2021
On Unbiased Score Estimation for Partially Observed Diffusions
We consider the problem of statistical inference for a class of partiall...
research
∙
03/09/2021
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo
Markov chain Monte Carlo (MCMC) is a powerful methodology for the approx...
research
∙
02/24/2021
On Unbiased Estimation for Discretized Models
In this article, we consider computing expectations w.r.t. probability m...
research
∙
01/27/2021
Log-Normalization Constant Estimation using the Ensemble Kalman-Bucy Filter with Application to High-Dimensional Models
In this article we consider the estimation of the log-normalization cons...
research
∙
11/09/2020
Multilevel Ensemble Kalman-Bucy Filters
In this article we consider the linear filtering problem in continuous-t...
research
∙
09/05/2020
Uncertainty modelling and computational aspects of data association
A novel solution to the smoothing problem for multi-object dynamical sys...
research
∙
08/18/2020
Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models
We consider the problem of parameter estimation for a class of continuou...
research
∙
04/08/2020
A Wasserstein Coupled Particle Filter for Multilevel Estimation
In this paper, we consider the filtering problem for partially observed ...
research
∙
03/10/2020
Unbiased Estimation of the Gradient of the Log-Likelihood in Inverse Problems
We consider the problem of estimating a parameter associated to a Bayesi...
research
∙
02/10/2020
Unbiased Filtering of a Class of Partially Observed Diffusions
In this article we consider a Monte Carlo-based method to filter partial...
research
∙
02/04/2020
Unbiased Estimation of the Solution to Zakai's Equation
In the following article we consider the non-linear filtering problem in...
research
∙
08/12/2019
Bayesian Inference for Latent Chain Graphs
In this article we consider Bayesian inference for partially observed An...
research
∙
07/15/2019
Multilevel Particle Filters for the Non-Linear Filtering Problem in Continuous Time
In the following article we consider the numerical approximation of the ...
research
∙
03/07/2019
Estimation and uncertainty quantification for the output from quantum simulators
The problem of estimating certain distributions over {0,1}^d is consider...
research
∙
12/04/2018
Bridging trees for posterior inference on Ancestral Recombination Graphs
We present a new Markov chain Monte Carlo algorithm, implemented in soft...
research
∙
10/11/2018
Central Limit Theorems for Coupled Particle Filters
In this article we prove a new central limit theorem (CLT) for coupled p...
research
∙
07/26/2018
Unbiased inference for discretely observed hidden Markov model diffusions
We develop an importance sampling (IS) type estimator for Bayesian joint...
research
∙
04/19/2018
On Large Lag Smoothing for Hidden Markov Models
In this article we consider the smoothing problem for hidden Markov mode...
research
∙
04/12/2018
Multilevel Particle Filters for Lévy-driven stochastic differential equations
We develop algorithms for computing expectations of the laws of models a...
research
∙
03/26/2018
On the loss of Fisher information in some multi-object tracking observation models
The concept of Fisher information can be useful even in cases where the ...
research
∙
11/08/2017
Multilevel Monte Carlo for Smoothing via Transport Methods
In this article we consider recursive approximations of the smoothing di...
research
∙
10/12/2017
